Nursing home evaluation system

ABSTRACT

Methods, systems, and devices are described for determining resource allocation in a resident care facility, like a nursing home facility. Embodiments of the invention provide assessment questions to an assessor via a computer interface. The assessment questions may be based on a base assessment model having questions relating to a number of resident care areas. Responses to the assessment questions may be received, some relating to answers provided to the assessor by respondents (e.g., residents or staff of the resident care facility). The responses may be processed to generate an assessment dataset, which may then be used to generate quality scores for the various resident care areas. The quality scores may indicate likelihoods of citation in the resident care areas as a function of data derived from the base assessment model. The quality scores and/or assessment results may then be graphically displayed and used to formulate a resource allocation determination.

CROSS REFERENCE

This application claims priority from co-pending U.S. Provisional PatentApplication No. 61/054,724, filed on May 20, 2008, entitled “NURSINGHOME EVALUATION SYSTEM,” which is hereby incorporated by reference inits entirety for all purposes.

Embodiments of the invention relate to resource allocation in generaland, in particular, to resource allocation for resident care facilities.

BACKGROUND

Often, government oversight of resident care facilities is used toprotect the residents of those facilities from abuse, lack of quality,and other environmental concerns. In certain cases, government oversightprograms use government surveyors to gather information from a facilityto identify areas of concern. These areas may be further investigatedfor non-compliance or other undesirable conditions. The investigationsmay result in issuance of citations to the facility.

While the government oversight programs may collect valuable types ofinformation from resident care facilities, many have argued that certainprograms involve large amounts of subjectivity, resulting in citationsbeing issued with little predictability, objectivity, or consistency.Further, many of the government oversight programs provide little usefulfeedback to the cited facilities, making it difficult for the facilitiesto improve. Without more information and more predictable results, itmay be difficult for facilities to take effective and efficient remedialmeasures and avoid future citations.

Thus, it may be desirable to provide nursing home managers with accessto more information for use in making resource allocationdeterminations, particularly relating to quality improvements.

SUMMARY

Among other things, methods, systems, and software are described fordetermining resource allocation in a resident care facility. Embodimentsof the invention provide resident care facilities with facilityassessment capabilities. One set of facility assessment capabilitiesprovided to the resident care facility may substantially mimic the datacollection and analysis of a base assessment model, like a governmentoversight program. Another set of facility assessment capabilities mayprovide additional types of data collection and analysis to assist aresident care facility in making resource allocation determinationsand/or to avoid citation.

In one embodiment, a method for generating information for determiningresource allocation in a nursing home facility is provided. Assessmentquestions are provided to an assessor via a computer interface, the setof assessment questions being based on the Quality Indicator Survey. TheQuality Indicator Survey comprises questions addressing a number ofresident care areas relating to choices, dignity, abuse, health,personal property, and quality; and the set of assessment questionsrelates to at least a portion of the resident care areas comprised inthe Quality Indicator Survey. Responses to the assessment questions arereceived via the computer interface, the responses being based onanswers provided to the assessor by respondents. The respondents mayinclude residents of the nursing home facility, relatives of residents,employees of the nursing home facility, or others. Quality scores aregenerated for each of the resident care areas based on the responses,each quality score being indicative of a likelihood of citation in thatresident care area as a function of data derived from the QualityIndicator Survey. Each quality score is graphically displayed inrelation to its resident care areas as a function of the data derivedfrom the Quality Indicator Survey. A resource allocation determinationis then formulated as a function of the quality scores.

In some other embodiments, a computer-readable storage medium isprovided. The computer-readable storage medium has computer-readablecode embodied in it for directing operation of a computer, thecomputer-readable code including instructions for generating informationfor determining resource allocation in a resident care facility. Theinstructions are in accordance with the following: providing a set ofassessment questions to an assessor via the computer, the set ofassessment questions being based on a base assessment model havingquestions relating to a number of resident care areas; receiving, viathe computer, responses to at least a portion of the set of assessmentquestions, at least a portion of the responses relating to answersprovided to the assessor by a set of respondents; processing theresponses to generate an assessment dataset; and generating a qualityscore for at least one of the resident care areas, the quality scorebeing based on the assessment dataset and indicative of a likelihood ofcitation in the resident care area as a function of data derived fromthe base assessment model. In certain embodiments, the instructions arefurther in accordance with displaying the quality score graphically inrelation to the data derived from the base assessment model; analyzingthe assessment dataset to generate an analytic dataset; or formulating aresource allocation determination as a function of the quality score.

BRIEF DESCRIPTION OF THE DRAWINGS

A further understanding of the nature and advantages of embodiments ofthe invention may be realized by reference to the following drawings. Inthe appended figures, similar components or features may have the samereference label. Further, various components of the same type may bedistinguished by following the reference label by a dash and a secondlabel, or by a lower-case character, that distinguishes among thesimilar components. If only the first reference label is used in thespecification, the description is applicable to any one of the similarcomponents having the same first reference label irrespective of thesecond reference label.

FIG. 1 shows a flow diagram of a method for determining resourceallocation in a resident care facility, according to various embodimentsof the invention.

FIG. 2 shows an embodiment of a method for graphically displayingquality score data, according to various embodiments of the invention.

FIG. 3A shows an illustrative graphical display of a quality score for aresident area, according to various embodiments of the invention.

FIG. 3B shows an illustrative graphical derivation of the firstboundary, according to various embodiments of the invention.

FIG. 3C shows an illustrative graphical derivation of the secondboundary, according to various embodiments of the invention.

FIG. 4 shows an illustrative flow diagram of drill down functionality,according to various embodiments of the invention.

FIG. 5 shows a simplified block diagram of an illustrative system fordetermining resource allocations in resident care facilities, accordingto various embodiments of the invention.

FIG. 6A shows an embodiment of a computational system for implementing anetwork interface portal, according to various embodiments of theinvention.

FIG. 6B shows an embodiment of a computational system for implementingan assessment client, according to various embodiments of the invention.

DETAILED DESCRIPTION

Typical examples of government oversight programs for resident carefacilities may involve various stages. One stage may provide for theconducting of audits by government regulatory agents to identify areasof potential concern. The audits may include assessments of residents,assessments of resident's relatives and/or friends, assessments offacility staff, assessor observations, and other information collection.Certain audit results in a particular area may trigger another stage, inwhich a more thorough investigation would be performed into that area(e.g., a “Stage II investigation”). If the more thorough investigationinto the area of concern unveils certain negative results (e.g.,statutory non-compliances), still another stage may be triggered, inwhich a citation could be issued against the facility.

Many have argued that much of the oversight process involves largeamounts of subjectivity, particularly during the information gatheringand analysis processes included in government audits. This subjectivitycould result in citations being issued with little predictability,objectivity, or consistency. Without predictable, objective, andconsistent results, it may be difficult for facilities to know how toimprove their quality and avoid future citations.

In the nursing home industry, for example, most states use a three-stageoversight program, like the one outlined above. Government surveyors maysurvey a facility to identify care areas of concern. Once identified, aStage II investigation may be triggered, which may result in a citation.Partly in response to concerns over subjectivity of these oversightprograms, the Quality Indicator Survey (“QIS”) was developed. The QIS,which claims to be more objective and resident-centered than thetraditional oversight models, has been, or is currently being, adoptedby a number of states in the United States.

Several aspects of the QIS, however, may limit its effectiveness withrespect to nursing home managers (e.g., boards, managers, supervisors,etc.). One such aspect of the QIS is the lack of information availableto the nursing home managers after an audit. For example, while nursinghome managers may be notified of failures (e.g., citations) in certaincare areas, they may not be provided with enough information todetermine the root causes of the citations, areas for improvement, etc.Another such aspect is the fact that nursing home managers may have towait for an audit to find out whether and where improvements are needed.For example, there may be no way for a nursing home manager toproactively predict areas where the nursing home may be audited.

For at least these reasons, it may be difficult for nursing homemanagers to determine how best to allocate resources. For example, amanager of a large conglomerate may focus on improving food choices forits residents after receiving complaints, while being unaware of a largeoccurrence of pressure ulcers among residents of a particular wing of aparticular facility. Currently, the nursing home may continue to beunaware of the problem until receiving a citation; and even then, thenursing home manager may be provided with too little information tooptimally address the cause of problem.

Among other things, methods, systems, and software are described fordetermining resource allocation in resident care facilities. Throughoutthe specification, embodiments of the invention will be described withreference to nursing home facilities. It will be appreciated, however,that, in addition to nursing home facilities, resident care facilitiesmay include orphanages, mental health facilities, hospitals, prisons, orany other facility where residents must be cared for by the staff of thefacility.

FIG. 1 shows a flow diagram of a method for determining resourceallocation in a resident care facility, according to various embodimentsof the invention. The method 100 begins when a nursing home decides toperform a facility assessment. In one case, the nursing home makes thisdetermination as a result of a self-imposed facility assessmentschedule. For example, a nursing home's management may decide toself-assess all or part of the nursing home facility each month. Inanother case, the facility assessment may be dictated by a statutorymandate. For example, a government regulation may mandate certain typesand/or frequencies of facility assessment to satisfy certain statutorycompliance. In yet another case, the nursing home may be forced orencouraged to perform one or more facility assessments by a third party.For example, a legal authority may mandate facility assessments as partof a citation or a lawsuit. In any of these or other cases, the nursinghome may begin at block 104 by identifying the target or targets of thefacility assessment. For example, a nursing home may opt to perform afacility assessment only on part of its facility (e.g., one wing or onefloor), a portion of its patients (e.g., patients with certainconditions or those identified in prior facility assessments), a portionof its properties (e.g., one of many nursing homes owned or operated bya single conglomerate), etc.

Before or after a target has been identified at block 104, an assessmentmay be generated at block 108 based on a base assessment model. In someembodiments, the generated assessment is the same, regardless of thetarget or targets identified. In other embodiments, the assessment isgenerated differently depending on a number of criteria. For example,the assessment may be generated with particular types of questionsdirected toward a certain medical condition of a target group ofresidents. In still other embodiments, the assessment is generated withparticular questions based on the types of assessment being performed.For example, assessment questions and/or formats may be tailored tointerviewing residents of the facility, interviewing relatives orfriends of residents of the facility, interviewing staff of thefacility, recording personal observations of the assessor regardingresidents or aspects of the facility, reviewing census sample records,reviewing admission records, or any other useful type of informationgathering.

Embodiments of the assessments generated at block 108 are based on abase assessment model. In certain embodiments, the base assessment modelincludes questions, question formats, and other information; while inother embodiments, the base assessment model includes information fromwhich assessment questions may be derived. Some embodiments of the baseassessment model include information taken or derived from a governmentassessment program. Some assessment programs may use certain measures todetermine characteristics of a resident care facility. For example, atraditional government survey model for nursing home facilities mayinclude a Minimum Data Set, having various quality measures and qualityindicators in thirty resident care area categories. Different types ofmeasures in the base assessment model may be used for different reasons.For example, the quality measures and quality indicators may help pointto areas of concern, which may warrant further investigation. Further,some types of measures are risk adjusted, such that certain measures mayonly apply to or may have different sensitivities for certain residentgroups. For example, a measure relating to incontinence may be evaluateddifferently (e.g., may be given more weight) for high risk residentsthan for low risk residents.

In one embodiment, the base assessment model includes the QIS. The QISmay include questions relating to a large number of resident care areasand resident care sub-areas. For example, the resident care areas mayinclude choices, dignity, abuse, health, personal property, quality, andothers. Resident care sub-areas in the resident care area of choices,for example, may be choice of activities, choice of food, etc. In somecases, questions may relate to a single resident care area or sub-area,while in other cases, questions may simultaneously relate to multipleresident care areas or sub-areas.

In some embodiments, the base assessment model may include otherinformation for use in generating the assessment. In certainembodiments, resident care facilities and/or other entities may addinformation to the base assessment model to influence futureassessments. For example, a nursing home may add certain questions toidentify where a resident resides within the nursing home facility(e.g., which floor), or how residents are responding to certaininitiatives established by the nursing home. Other embodiments of thebase assessment model may include information from other assessmentmodels, information from past assessments, information relating toprevious assessments and/or citations, or any other useful information.

Once the assessment has been generated at block 108, each target may beassessed in block 112 to generate assessment results. The assessmentresults may include answers to assessment questions, typically in someraw format. For example, a question may seek a yes or no answer byproviding a selectable radio button on a graphical user interface(“GUI”). When the “NO” radio button is selected, the GUI may set a flagto “0,” and when the “YES” radio button is selected, the GUI may set aflag to “1.” The assessment results may simply include a “0” or “1” forthat question. In some embodiments, the assessment results are stored ina flat data structure (e.g., in a flat file database), while in otherembodiments, the assessment results are stored in a relational datastructure (e.g., in a relational database with various dimensionalattributes).

Embodiments of the method 100 may process the assessment results inblock 116 to generate one or more assessment datasets. In someembodiments, the assessment dataset consists of processed versions ofthe assessment results (e.g., the answers to the assessment questions).For example, the assessment dataset may include a relational database ofassessment results, configured to be data mined (e.g., filtered, sorted,searched, etc.). In other embodiments, the assessment dataset includesother information relating to the assessment. For example, theassessment dataset may include time information (e.g., how long theassessment took to conduct, at what time and on what date the assessmentwas conducted, etc.), assessor information (e.g., the assessor's nameand other identifiers or qualifiers), facility information (e.g., anidentifier for the facility within a conglomerate, a location identifierwithin the facility, the age, location, size, or another characteristicof the facility, etc.), file information (e.g., file type, file size,file name, etc.), or any other useful assessment-related information. Itwill be appreciated that, where multiple targets are assessed, it may benecessary or desirable to generate multiple assessment datasets. Wheremultiple assessment datasets are generated, the different assessmentdatasets may include different types of information or have otherdifferent characteristics.

In certain embodiments, the assessment results and/or the assessmentdataset are evaluated for one or more reasons at block 120. In oneembodiment, the assessment results are evaluated to determine whetherthe data is in a proper format, whether some or all of the questionshave been answered, whether the data has been properly stored and/oruploaded to a server, or any other data auditing function. In anotherembodiment, certain data goals are set (e.g., a certain number ofresidents to sample), and the assessment dataset is evaluated todetermine whether the data goals have been met. In certain embodiments,where the evaluation in block 120 fails, it may be desirable to performadditional assessments or choose new targets to supplement or supplantassessment data that has already been collected.

In some embodiments, the survey dataset is used in block 128 to generateone or more quality scores. In certain embodiments, each quality scorerelates to a resident care area, a resident care sub-area, or somecombination thereof. In one embodiment, a quality score provides anindication of a level of quality from one to one-hundred, as determinedby a set of assessment questions relating to a particular resident carearea in an assessed resident care facility. For example, in anassessment, thirty residents are asked a set of assessment questionsrelating to choices, and only three residents give negative responses.An illustrative quality score may be calculated by:

${{Quality}\mspace{14mu} {Score}} = {{100 - \left( {\frac{{Negative}\mspace{14mu} {results}}{{Total}\mspace{14mu} {results}}*100} \right)} = {{100 - \left( {\frac{3}{30}*100} \right)} = 90.}}$

It will be appreciated that many ways are possible for calculating aquality score according to embodiments of the invention. For example,the calculation may be based on positive results, combinations ofresults, or more complex algorithms (e.g., statistical processing,etc.). In some embodiments, comparison data is retrieved in block 124,which may affect the calculation of quality scores in block 128. Thecomparison data may provide baseline or normalization information forthe quality score calculation, or additional data to make thecalculation more precise or useful. In certain embodiments, thecomparison data is derived from the base assessment model, while inother embodiments, the comparison data is derived from another source ofstored data. In one embodiment, the quality score calculation may dependon statutory information stored as part of the base assessment model. Inanother embodiment, past assessment results or assessment datasets frompast assessments may be used to calculate or refine the calculation ofquality scores. For example, the comparison data may include assessmentresults and/or datasets from past assessments of the same or a differentresident care facility, the same or a different sample or geographiclocation within a resident care facility, the same or a differentassessor, etc.

Various embodiments of the method 100 provide different types offunctionality for using the quality scores generated in block 128. Insome embodiment, the quality scores may be graphically displayed inblock 132. It will be appreciated that there are many ways tographically display data, including using bar charts, histograms, linegraphs, pie charts, etc. One embodiment of a method for graphicallydisplaying the quality score data is shown in FIG. 2.

The method 200 in FIG. 2 begins at block 204 by displaying a graphicalscale indicating the full range of possible quality scores. For example,the graphical scale may indicate that the quality scores range from oneto one-hundred. Further, in certain cases, the graphical scale may alsobe linear or non-linear, and may include indicia of one or more pointson the scale (e.g., a hash mark to indicate intervals of ten qualitypoints).

At block 208, a first threshold quality score is received. In someembodiments, the first threshold quality score is derived from the baseassessment model. For example, the QIS may indicate that governmentsurveyors must perform a Stage II investigation into a resident carearca, whenever the quality score is less than a particular mandatedthreshold number. These mandated threshold numbers may be included inthe base assessment model, when the base assessment model includes theQIS. For example, the base assessment model may dictate that the firstthreshold quality score in the “choices” resident care area isforty-seven, a number which may be derived from or equal to the mandatedthreshold number for that resident care area. It is worth noting thatthe generated quality scores (e.g., those generated in block 128 ofFIG. 1) may not directly correlate to similar types of values in thebase assessment model (e.g., the scales may be different or inverted, ormay record different numbers of significant digits). As such, it may benecessary or desirable to normalize, or otherwise adjust the values forthem to correlate appropriately.

In other embodiments, the first threshold quality score is derived fromcalculations relating to positive predictive value (“PPV”). For example,in some government oversight programs, the assessment data (e.g., surveydata) may be collected to determine where it would be mostcost-effective to perform a further investigation (e.g., a Stage IIinvestigation). This determination may include an evaluation of theprobability of issuing a citation in an area (e.g., findingnon-compliance) as a result of the further investigation. As such, itmay be desirable to determine which quality scores in a particularresident care area result in citations and how often. Using this data,it may be possible to calculate the PPV of certain quality scores, e.g.,the probability that a given quality score in that resident care areawill result in a citation in that care area. PPVs of various possiblequality scores may then be determined (e.g., by looking at data from thebase assessment model or other comparison data). In one embodiment,these PPVs are evaluated to determine which of the possible qualityscores yields (or would yield) the largest PPV for issuing a citationafter a Stage II investigation.

It will be appreciated that, depending on the amount and type ofavailable data, it may not be possible to calculate PPVs for allpossible quality scores in a given resident care area or sub-area. Assuch, it may be desirable to interpolate, extrapolate, or otherwisegenerate data for those scores (e.g., statistically). Similarly, it isworth noting that quality score data may not exist in a base assessmentmodel for all the data collected during a facility assessment. Forexample, the assessment may generate quality scores for resident caresub-areas, while the base assessment model may only include mandatedthreshold numbers for resident care areas. In these and other cases, itmay be desirable to generate threshold numbers for use as firstthreshold quality scores. In one embodiment, the first threshold qualityscore derived for a resident care area is applied as the first thresholdquality score for all its resident care sub-areas. In other embodiments,data from the base assessment model and/or the comparison data is usedto calculate the first threshold quality score for resident caresub-areas (e.g., by finding PPVs, as discussed above).

In some embodiments, it may be desirable to graphically display regionswith respect to the graphical scale displayed at block 204. At block212, a first region may be displayed, indicating the range of possiblequality scores falling below the first threshold quality score, inrelation to the graphical scale. In certain embodiments, the firstregion may indicate a range of quality scores, which, if received fromthe base assessment model (e.g., from a government survey), would carrya substantially high likelihood of some follow-on action (e.g., afurther investigation or a citation). In one embodiment, the firstregion indicates the range of quality scores for a particular residentcare area that would automatically trigger a Stage II investigation ifreceived from QIS results.

In some embodiments of the method 200, an upper region is displayed,indicating the range of possible quality scores falling above the firstthreshold quality score, in relation to the graphical scale. In certainembodiments, the upper region indicates the range of possible qualityscores falling above the first threshold quality score, but below asecond threshold quality score. The second threshold quality score maybe calculated in block 216 in any useful way, depending on the type ofinformation desired. In one embodiment, the second threshold qualityscore is calculated using the PPVs of the various possible qualityscores for a particular resident care area or sub-area. For example,PPVs may be evaluated to determine a second threshold quality score thatwould yield the greatest positive difference between the sum of all PPVsof scores within the upper region falling above the second thresholdquality score and the sum of all PPVs of scores within the upper regionfalling below the first threshold quality score.

After generating the second threshold quality score in block 216, it maybe desirable to display regions relating to the second threshold qualityscore. In some embodiments, a second region is displayed in block 220,indicating the range of possible quality scores falling above the firstthreshold quality score and below the second threshold quality score, inrelation to the graphical scale. Further, in some embodiments, a thirdregion is displayed in block 224, indicating the range of possiblequality scores falling above the second threshold quality score, inrelation to the graphical scale. In one embodiment, the second regionindicates the range of quality scores for a particular resident carearea that carry a reasonable likelihood of triggering a Stage IIinvestigation if received from QIS results; while the third regionindicates the range of quality scores for the particular resident carearea that are substantially unlikely to trigger a Stage II investigationif received from QIS results.

Embodiments of the method 200 display an indicator at block 228,indicating the location of the quality score for a particular residentcare area or sub-area that was generated from the facility assessment(e.g., in block 128 of FIG. 1). In certain embodiments, the indicator isdisplayed in relation to the graphical scale and/or the displayedregions. It will be appreciated that there are many ways to display thegraphical scale, the various regions, and/or the indicators. Further, itwill be appreciated that various other types of labels, indicia, and/orother elements may be included to enhance or adapt the display forvarious reasons. For example, each region may be color-coded forenhanced viewing.

FIG. 3A shows an illustrative graphical display of a quality score for aresident area, according to various embodiments of the invention. Agraphical scale 320 is displayed, indicating all possible quality scoresfor the resident care area of “abuse.” The graphical scale 320 includesa first region 322-1, a second region 322-2, and a third region 322-3.The first threshold quality score is displayed as a first boundary 324between the first region 322-1 1 and the second region 322-2, and thesecond threshold quality score is displayed as a second boundary 326between the second region 322-2 and the third region 322-3.

For illustrative purposes, FIG. 3A shows example data derived fromcomparison data for the “abuse” resident care area. Each data point 310indicates a quality score received from the results of a QIS assessment,and whether a citation ultimately resulted (i.e., a “1” indicates that acitation resulted, and a “0” indicates that no citation resulted). Forexample, a first data point 310-1 indicates that a quality score of zeroresulted in no citation; a second data point 310-2 indicates that aquality score of ten resulted in a citation; and a third data point310-3 and a fourth data point 310-4 indicate that a quality score oftwenty resulted in a citation in one instance and no citation in anotherinstance, respectively.

The first boundary 324 (i.e., the boundary between the first region322-1 and the second region 322-2) may correspond to the thresholdmeasure in the QIS base assessment model for triggering a Stage IIinvestigation into the “abuse” resident care area. In the illustratedembodiment, the first boundary 324 is set at a point that maximizes thePPV of the Stage II investigation trigger. An illustrative graphicalderivation of the first boundary 324 is shown in FIG. 3B.

FIG. 3B shows a graph of average PPVs for each of a series of qualityscores derived from a base assessment model, according to the data shownin FIG. 3A. The graph 350 shows average PPV data 360 according to a PPVaxis 352 versus a quality score axis 354. The graph 350 further shows anaverage PPV data point 362, derived at each data point 310 provided inFIG. 3A.

In this illustrative embodiment, the average PPV data points 362 arecalculated for each quality score by averaging the PPV data for thatquality score with the PPV of all the quality scores below it. Forexample, at the fourth data point 310-4 of FIG. 3A, the average PPV maybe calculated by averaging the data from the first data point 310-1, thesecond data point 310-2, the third data point 310-3, and the fourth datapoint 310-4. As discussed above, these data may yield results of “0,”“1,” “1,” and “0,” respectively, which averages to an average PPV of0.5. This average PPV may indicate that, according to past data, aquality score between zero and twenty (i.e., the quality scorecorresponding to the fourth data point 310-4) carries an approximatelyfifty-percent chance of yielding a citation in the “abuse” resident carearea.

It is worth noting that the maximum average PPV, according to FIG. 3B isaround fifty-six-percent, corresponding to a quality score of forty-five(i.e., the second average PPV data point 362-2). In some embodiment, thefirst boundary 324 in FIG. 3A would then be set to forty-five,corresponding to this maximum average PPV. In other embodiments, thefirst boundary 324 is set to a different value close to the maximumaverage PPV. For example, the first boundary 324 is set in FIG. 3A toapproximately forty-six, slightly higher than the maximum average PPV.Setting the first boundary 324 in this location may indicate that thatthere is approximately a fifty-six-percent chance that a nursing homefacility that triggers a Stage II investigation under the QIS for the“abuse” resident care area will ultimately be issued a citation for thatresident care area.

It is worth noting that the calculation of average PPV in someembodiments is more complex for one or more reasons. In someembodiments, the correlation between quality scores and citations for aresident care area are influenced by data from multiple resident careareas (e.g., where some questions or some information overlaps) or fromdifferent types of assessments. For example, portions of the “abuse”resident care area may be investigated in resident interviews, assessorobservations, and family interviews. In these cases, an overalllikelihood of citation may be calculated as a function of the union ofvarious corresponding PPVs.

In some embodiments of the graphical scale 300 of FIG. 3A, the secondboundary 324 is determined by attempting to maximize the positivedifference between the average PPV of the second region 322-2 and theaverage PPV of the third region 322-3. An illustrative graphicalderivation of the second boundary 324 is shown in FIG. 3C. FIG. 3C showsa graph of average PPVs for each of a series of quality scores,according to the data above the first boundary 324 shown in FIG. 3A.

The graph 370 shows data according to a PPV axis 372 versus a qualityscore axis 374. A first data series 380 is shown on the graph 370, andincludes a first series average PPV data point 382 at each data point310 provided in FIG. 3A that exceeds the first boundary 324. Each of thefirst series average PPV data points 382 indicates the average PPV forthe data points 310 from the first data point 310 above the firstboundary 324 (i.e., at a quality score of forty-eight, in thisillustrative case) to the data point 310 correlating to the first seriesaverage PPV data point 382. For example, the sixth first series averagePPV data point 382-1 indicates an average PPV of around fifty percentfor quality scores ranging from forty-eight to seventy-two.

A second data series 385 is shown on the graph 370, and includes asecond series average PPV data point 387 at each data point 310 providedin FIG. 3A that exceeds the first boundary 324. Each of the secondseries average PPV data points 382 indicates the average PPV for thedata points 310 from the data point 310 correlating to the second seriesaverage PPV data point 387 to the highest available data point 310(i.e., at a quality score of ninety-eight, in this illustrative case).For example, the sixth second series average PPV data point 387-1indicates an average PPV of around twenty-nine percent for qualityscores ranging from seventy-two to ninety-eight.

The graph 370 further illustrates difference bars 390 at each data point310 provided in FIG. 3A that exceeds the first boundary 324. Eachdifference bar 390 indicates the difference, for each data point 310,between the corresponding first series average PPV data point 382 andthe corresponding second series average PPV data point 387. The largestpositive value of this difference may indicate a location at which thereis a substantial difference in PPV between quality scores above thedifference and those below the difference. As such, in some embodiments,the second boundary 326 is set at or near the data point 310 having thelargest positive average PPV difference.

In this illustrative embodiment, the average PPV at the eighth firstseries average PPV data point 382-2 (i.e., corresponding to a qualityscore of eighty-five) may be calculated again as approximatelyfifty-percent, but the average PPV at the eighth second series averagePPV data point 387-2 may be calculated as approximately twenty percent.As such, the eighth difference bar 390-2 indicates a positive averagePPV difference of approximately twenty percent, which may be the largestpositive value of all the difference bars 390. It is worth noting thatthe second boundary 326 in FIG. 3A is set slightly above thecorresponding location on the graphical scale 320, at approximatelyeight-seven.

In some embodiments of the graphical scale 300 of FIG. 3A, an indicator330 is shown, indicating the quality score generated from the facilityassessment for the resident care area. As illustrated, the indicator 330indicates a generated quality score of approximately seventy-six for the“abuse” resident care area. According to the elements of the graphicalscale 300, it may be clear that the indicator 330 falls within thesecond region 322-2. As such, the indicator 330 may indicate that, if aQIS assessment were performed at the nursing home facility at this time,there would be some likelihood, though not a substantially highlikelihood, that any investigation into the resident care area of“abuse” would result in a citation in that area.

Returning to FIG. 1, embodiments of the method 100 provide differenttypes of functionality in addition to graphically displaying qualityscores, as in block 132. In some embodiments, the quality scores areused to make a resource allocation determination in block 136. Theresource allocation may include the allocation of financial resources,staff resources, time, and/or any other types of resources. In someembodiments, resource allocation determinations arc made among variousresident care areas within a single resident care facility. Otherembodiments provide for many other types of resource allocationdeterminations. In one embodiment, information is used to determineresource allocations among various sections (e.g., wings, cell blocks,departments, etc.) of a resident care facility. In another embodiment,information is used by managers of multiple resident care facilities(e.g., franchises, subsidiaries, conglomerates, etc.) to determineresource allocations among the various resident care facilities. Forexample, resource allocation determinations may be made by geographiclocation, facility size, facility type, on a per-facility basis, or inany other useful way.

In some embodiments, the resource allocation determination may begenerated in block 136 completely or partially by human analysis ofassessment data, for example, including the quality scores generated inblock 128. In other embodiments, all or part of the resource allocationdetermination is generated automatically (e.g., by computer). It will beappreciated that the resource allocation determination may involve anumber of factors, which may or may not be directly associated with theassessment data. For example, resource allocation determinations may beinfluenced by time of year, company goodwill, financial conditions,access to particular resources (e.g., specially trained staff), internalor external pressure (e.g., from a board of directors or a particulargroup of residents), etc.

Some embodiments of the method 100 may provide functionality to generatecertain analytics from the assessment data, for example, including thequality scores, in block 140. The analytics generated in block 140 mayinclude any useful type of data processing. For example, the analyticsmay include database analysis functions (e.g., sorting, filtering,parsing, etc.) or statistical processing functions (e.g., Bayesiananalyses, correlations, line fitting, predictive algorithms,interpolation and extrapolation, etc.). In certain embodiments, theanalytics generated in block 140 may be used to generate a resourceallocation determination, as in block 136.

In various embodiments of the method 100, reports are generated in block144. It may be desirable to generate one or more different types ofreports for many different reasons. In certain embodiments, reportgeneration may include formatting generated data for output. Forexample, some or all of the data generated in blocks 112, 116, 120, 124,128, 132, 136, and/or 140 may be formatted for output as a file, forprinting, for uploading to the Internet, or for any other useful type ofreporting.

In some embodiments, the method may provide functionality to drill downto various levels of data in block 148. FIG. 4 shows an illustrativeflow diagram of drill down functionality, according to variousembodiments of the invention. The method 400 begins in block 404 byreceiving assessment data. The assessment data may be any data generatedor used in relation to the facility assessment, including, for example,data from blocks 112, 116, 120, 124, 128, 132, 136, and/or 140 of FIG.1.

Once the assessment data has been generated and/or received, it may bedesirable to use the data in a number of different ways. Some of thosedata uses may be effectuated or enhanced by providing the ability todrill down to different levels of data. Drilling down may include usingone or more data processing functions (e.g., sorting, filtering,statistical processing, etc.) to allow viewing and/or analysis ofcertain portions of the data having certain characteristics. In someembodiments, the method 400 provides functionality to drill down to thefacility level in block 408 (e.g., to look at one facility in comparisonto other facilities within a conglomerate, competing facilities, averagefacilities, baseline facilities, etc.), to the facility section level inblock 412 (e.g., to be able to compare sections of a particular facilityby wing, property, floor, department, staff group, resident group,specialty, etc.), to the resident care area level in block 416 (e.g., tobe able to compare how a facility is performing in certain resident careareas versus other resident care areas, etc.), to the resident caresub-area level in block 420 (e.g., to be able to compare how a facilityis performing in certain resident care sub-areas versus other residentcare sub-areas, etc.), to the question level in block 424 (e.g., to beable to compare how certain questions are answered among differentresidents or at different times, to compare among related questionsaddressing similar areas of potential concern, etc.), to the individuallevel in block 428 (e.g., to be able to compare assessment results amongindividual residents, among individual staff members, among individualfamily members of residents, etc.), and or any other types of usefuldrill down.

For example, a facility assessment results in a low quality score forthe “choices” care area. Drilling down to the resident care sub-area,facility section, question, and individual levels reveals that thelowest scores seem to come from residents on the third floor complainingthat evening activities do not meet their interests. A quick follow-upwith those residents further reveals that many of them enjoy the cardgame, Bridge, and some others are eager to learn. It may be desirable inthat case for the resident care facility to simply add Bridge to itslist of evening activities. It is worth noting that the ability to drilldown to different levels of the data may allow for more efficient andeffective resource allocations in many instances.

It will be appreciated that many other types of drill downs arepossible, including drilling down to other categories of data, groups ofcategories, hierarchies and/or sorts of categories, etc. It will befurther appreciated that, after each drill down (or a series of drilldowns), it may be desirable to regenerate certain assessment data. Forexample, as shown in FIG. 1, the drilled down data may be passed back toblocks 132, 136, 140, and/or 144 to regenerate one or more types ofassessment data. It will be even further appreciated that some or all ofthe assessment data (e.g., the resource allocation determinationsgenerated in block 136 and the reports generated in block 144) may beultimately used to allocate resources in block 152.

Some embodiments of the invention are implemented in systems forallocating resources. In certain embodiments, the systems are operableto perform embodiments of the methods, like those described withreference to FIGS. 1-4. FIG. 5 shows a simplified block diagram of anillustrative system for determining resource allocations in residentcare facilities, according to various embodiments of the invention.

The system 500 includes a network portal interface 510, operable toprovide one or more assessor clients 532 with access to assessment dataand functionality via a network 530. The assessor clients 532 mayinclude any type of device or system operable to interface with thenetwork 530 and the network portal interface 510. For example, anassessor client 532 may be include a laptop, a personal digitalassistant (“PDA”), a cellular telephone, a tablet computer, etc. In someembodiments, the assessor client 532 logs in to the network portalinterface 510 to gain access to the assessment data and/orfunctionality. For example, the assessor client 532 may transmit logindata (e.g., a user name and password, biometrics, etc.) over the network530 for authentication.

The network 530 may include any type of network operable to communicatedata between the assessor clients 532 and the network portal interface510. For example, the network 530 may include a local area network, awide area network, the Internet, a cellular network, a wireless network,a fiber-optic network, a secure network (e.g., a virtual privatenetwork), or any other type of network known in the art. Further, insome embodiments, the network 530 includes data security functionality.In certain embodiments, the data security functionality includes securenetwork transmissions (e.g., network encryption, secure socket layer,etc.). In other embodiments, the data security functionality includesfile-level security (e.g., file encryption, secure servers, passwordprotection, etc.). In certain embodiments, the data securityfunctionality is configured to provide data privacy and/or security asgoverned by a mandate. For example, the mandate may include a corporatemandate (e.g., a corporate privacy policy), a government mandate (e.g.,the Health Insurance Portability and Accountability Act (“HIPAA”), theEuropean Union Data Directive, etc.), etc.

Embodiments of the network portal interface 510 provide access toassessment data and assessment functionality. In some embodiments, theassessment data includes a base assessment model 522 and comparison data524. In certain embodiments, the assessment data is stored on one ormore servers 520, accessible to the network portal interface 510 (e.g.,directly, over a network, etc.). The one or more servers 520 may includesecure servers, networked servers, flat-file or relational databases,and/or any other useful data storage and access functionality. In someembodiments, the servers 520 are local to the facility performing theassessment, while in other embodiments, the servers 520 are remote. Forexample, a resident care facility may store its comparison data 524 andpart of its base assessment model 522 on a local computer in an on-sitemanagement office, while the remainder of the base assessment model 522is stored in a central government server.

The base assessment model 522 may include information from which anassessment (e.g., assessment questions and formats) may be derived, insome cases according to a government or predefined assessment program.In one embodiment, the base assessment model 522 includes the QIS,and/or information relating to the QIS. In certain embodiments, residentcare facilities and/or other entities may add information to the baseassessment model 522 to influence future assessments.

The comparison data 524 may include information from other assessmentmodels, information from past assessments, information relating toprevious assessments and/or citations, or any other useful informationfor comparing the results of an assessment or otherwise affecting thevalue of the results. For example, the comparison data 524 may providebaseline or normalization information for the quality score calculation,or additional data to make the calculation more precise or useful. Incertain embodiments, the comparison data 524 is derived from the baseassessment model 522, while in other embodiments, the comparison data524 is derived from another source of stored data. In variousembodiments, the comparison data 524 may include assessment resultsand/or datasets from past assessments of the same or a differentresident care facility, the same or a different sample or geographiclocation within a resident care facility, the same or a differentassessor, etc.

In some embodiments, the network portal interface 510 providesassessment-related functionality through one or more functional units.These functional units may, individually or collectively, be implementedwith one or more Application Specific Integrated Circuits (ASICs)adapted to perform some or all of the applicable functions in hardware.Alternatively, the functions may be performed by one or more otherprocessing units (or cores), on one or more integrated circuits. Inother embodiments, other types of integrated circuits may be used (e.g.,Structured/Platform ASICs, Field Programmable Gate Arrays (FPGAs), andother Semi-Custom ICs), which may be programmed in any manner known inthe art. The functions of each unit may also be implemented, in whole orin part, with instructions embodied in a memory, formatted to beexecuted by one or more general or application-specific processors.

One such functional unit that is included in embodiments of the system500 is a response processing unit 540. The response processing unit 540may be operable to receive sets of assessment responses and processthem, for example, to generate one or more assessment datasets. Theassessment datasets may include processed versions of the assessmentresults (e.g., the answers to the assessment questions in a relationaldatabase, etc.), information relating to the assessment (e.g., timeinformation, assessor information, facility information, fileinformation, etc.), or any other useful information.

Embodiments of the response processing unit 540 may be operable togenerate relational and/or flat-file databases of assessment responses,audit assessment data (e.g., determine whether the data is in a properformat, whether some or all of the questions have been answered, whetherthe data has been properly stored and/or uploaded to a server, evaluatewhether certain assessment data goals have been met, etc.), etc. In someembodiments, the response processing unit 540 is operable to generateone or more quality scores, in some cases relating to a resident carearea, a resident care sub-area, or some combination thereof.

The response processing unit 540 and/or the network portal interface 510may be in communication with other functional units, including a displaygeneration unit 550, an allocation determination unit 560, an analyticsunit 570, and a report generation unit 580. Various embodiments of thedisplay generation unit 550 are operable to generate and/or outputdisplays of assessment-related information. For example, the displaygeneration unit 550 may be configured to generate graphical displays ofassessment data, quality scores, comparison data, base assessment modeldata, etc. Various embodiments of the allocation determination unit 560are operable to determine resource allocations from assessment-relatedinformation. For example, the allocation determination unit 560 may beconfigured to determine the allocation of financial resources based onquality scores. Various embodiments of the analytics unit 570 areoperable to perform analytics on assessment-related information. Forexample, the analytics unit 570 may be configured to perform variousdatabase analysis functions (e.g., sorting, filtering, parsing, etc.) orstatistical processing functions (e.g., Bayesian analyses, correlations,line fitting, predictive algorithms, interpolation and extrapolation,etc.).

Various embodiments of the report generation unit 580 are operable togenerate and/or output reports of assessment-related information. Forexample, the report generation unit 580 may be configured to reportassessment data, quality scores, comparison data, base assessment modeldata, displays generated by the display generation unit 550, resourceallocation determinations generated by the allocation determination unit560, analytics generated by the analytics unit 570, etc. In someembodiments, the report generation unit 580 is operable to generatereports formatted for output as a file, for printing, for uploading tothe Internet, or for any other useful type of reporting. Further, incertain embodiments, the report generation unit 580 is operable toprovide functionality to drill down to various levels of data forviewing and/or reporting.

It will be appreciated that the various components of the system 500 maybe implemented in a number of ways according to embodiments of theinvention. In some embodiments, the blocks of the system 500 areimplemented as separate hardware components or as functional blockswithin one or more hardware components. In other embodiments, some orall of the functionality of the system 500 is implemented ascomputer-readable instructions stored on a computational medium, or assome other form of computational system.

Illustrative computational systems for implementing embodiments of theinvention are shown in FIGS. 6A and 6B, respectively. It should be notedthat FIGS. 6A and 6B are meant only to provide generalized illustrationsof various components, any or all of which may be utilized asappropriate. FIGS. 6A and 6B, therefore, broadly illustrate howindividual system elements may be implemented in a relatively separatedor relatively more integrated manner.

FIG. 6A shows an embodiment of a computational system for implementing anetwork interface portal, according to various embodiments of theinvention. In some embodiments, the computational system 600 may beoperable to implement the network interface portal 510 of FIG. 5. Thecomputational system 600 is shown having hardware elements that may beelectrically coupled via a bus 626 (or may otherwise be incommunication, as appropriate). The hardware elements may include one ormore processors 602, including without limitation one or moregeneral-purpose processors and/or one or more special-purpose processors(such as digital signal processing chips, graphics acceleration chips,and/or the like); one or more input devices 604, which can includewithout limitation a mouse, a keyboard, and/or the like; and one or moreoutput devices 606, which can include without limitation a displaydevice, a printer, and/or the like.

The computational system 600 may further include (and/or be incommunication with) one or more storage devices 608, which can comprise,without limitation, local and/or network accessible storage and/or caninclude, without limitation, a disk drive, a drive array, an opticalstorage device, a solid-state storage device such as a random accessmemory (“RAM”), and/or a read-only memory (“ROM”), which can beprogrammable, flash-updateable, and/or the like. The computationalsystem 600 might also include a communications subsystem 614, which caninclude without limitation a modem, a network card (wireless or wired),an infra-red communication device, a wireless communication deviceand/or chipset (such as a Bluetooth device, an 802.11 device, a WiFidevice, a WiMax device, cellular communication facilities, etc.), and/orthe like. The communications subsystem 614 may permit data to beexchanged with a network (e.g., the network 530 of FIG. 5), and/or anyother devices described herein. In many embodiments, the computationalsystem 600 will further comprise a working memory 618, which can includea RAM or ROM device, as described above.

The computational system 600 also may include software elements, shownas being currently located within the working memory 618, including anoperating system 624 and/or other code, such as one or more applicationprograms 622, which may include computer programs of embodiments of theinvention, and/or may be designed to implement methods of embodiments ofthe invention and/or configure systems of embodiments of the invention,as described herein. For example, the application programs 622 mayinclude functionality to implement the response processing unit 540, thedisplay generation unit 550, the allocation determination unit 560, theanalytics unit 570, and/or the report generation unit 580 of FIG. 5.

Merely by way of example, one or more procedures described with respectto the method(s) discussed above might be implemented as code and/orinstructions executable by a computer (and/or a processor within acomputer). A set of these instructions and/or code might be stored on acomputer readable storage medium 610 b. In some embodiments, thecomputer readable storage medium 610 b is the storage device(s) 608described above. In other embodiments, the computer readable storagemedium 610 b might be incorporated within a computational system, suchas the system 600. In still other embodiments, the computer readablestorage medium 610 b might be separate from the computational system(i.e., a removable medium, such as a compact disc, etc.), and/orprovided in an installation package, such that the storage medium can beused to configure a general purpose computer with the instructions/codestored thereon. These instructions might take the form of executablecode, which is executable by the computational system 600 and/or mighttake the form of source and/or installable code, which, upon compilationand/or installation on the computational system 600 (e.g., using any ofa variety of generally available compilers, installation programs,compression/decompression utilities, etc.), then takes the form ofexecutable code. In these embodiments, the computer readable storagemedium 610 b may be read by a computer readable storage media reader 610a.

In one embodiment, the invention employs a computational system (such asthe computational system 600) to perform methods of embodiments of theinvention. According to a set of embodiments, some or all of theprocedures of such methods are performed by the computational system 600in response to processor 602 executing one or more sequences of one ormore instructions (which might be incorporated into the operating system624 and/or other code, such as an application program 622) contained inthe working memory 618. Such instructions may be read into the workingmemory 618 from another machine-readable medium, such as one or more ofthe storage device(s) 608 (or 610). Merely by way of example, executionof the sequences of instructions contained in the working memory 618might cause the processor(s) 602 to perform one or more procedures ofthe methods described herein. In this way, the computational system 600can be “configured to” or “operable to” perform any number of suchprocedures or methods.

The terms “machine readable medium ” and “computer readable medium,” asused herein, refer to any medium that participates in providing datathat causes a machine to operate in a specific fashion. In an embodimentimplemented using the computational system 600, various machine-readablemedia might be involved in providing instructions/code to processor(s)602 for execution and/or might be used to store and/or carry suchinstructions/code (e.g., as signals). In many implementations, acomputer readable medium is a physical and/or tangible storage medium.Such a medium may take many forms, including but not limited to,non-volatile media, volatile media, and transmission media. Non-volatilemedia includes, for example, optical or magnetic disks, such as thestorage device(s) (608 or 610). Volatile media includes, withoutlimitation dynamic memory, such as the working memory 618. Transmissionmedia includes coaxial cables, copper wire, and fiber optics, includingthe wires that comprise the bus 626, as well as the various componentsof the communication subsystem 614 (and/or the media by which thecommunications subsystem 614 provides communication with other devices).Hence, transmission media can also take the form of waves (includingwithout limitation radio, acoustic and/or light waves, such as thosegenerated during radio-wave and infra-red data communications).

Common forms of physical and/or tangible computer readable mediainclude, for example, a floppy disk, a flexible disk, a hard disk,magnetic tape, or any other magnetic medium, a CD-ROM, any other opticalmedium, punchcards, papertape, any other physical medium with patternsof holes, a RAM, a PROM, an EPROM, a FLASH-EPROM, any other memory chipor cartridge, a carrier wave as described hereinafter, or any othermedium from which a computer can read instructions and/or code.

Various forms of machine-readable media may be involved in carrying oneor more sequences of one or more instructions to the processor(s) 602for execution. Merely by way of example, the instructions may initiallybe carried on a magnetic disk and/or optical disc of a remote computer.A remote computer might load the instructions into its dynamic memoryand send the instructions as signals over a transmission medium to bereceived and/or executed by the computational system 600. These signals,which might be in the form of electromagnetic signals, acoustic signals,optical signals, and/or the like, are all examples of carrier waves onwhich instructions can be encoded, in accordance with variousembodiments of the invention.

The communications subsystem 614 (and/or components thereof) generallymay receive the signals, and the bus 626 then may carry the signals(and/or the data, instructions, etc. carried by the signals) to theworking memory 618, from which the processor(s) 602 may retrieve andexecute the instructions. The instructions received by the workingmemory 618 may optionally be stored on a storage device 608 eitherbefore or after execution by the processor(s) 602.

It will be apparent to those skilled in the art that substantialvariations may be made in accordance with specific requirements. Forexample, customized hardware might also be used, and/or particularelements might be implemented in hardware, software (including portablesoftware, such as applets, etc.), or both. Further, connection to othercomputing devices such as network input/output devices may be employed.

FIG. 6B shows an embodiment of a computational system for implementingan assessment client, according to various embodiments of the invention.In some embodiments, components of the client terminal 650 are similarto respective components of the computational system 600 of FIG. 6A.However, the client terminal 650 includes application programs 672directed to implement functions of an assessment client (e.g., 532 ofFIG. 5).

In certain embodiments, the application programs 672 provide interfacefunctionality, operable to interface the client terminal 650 with anetwork interface portal. In other embodiments, the application programs672 provide a graphical user interface through which a user of theclient terminal 650 may interact with the client terminal 650. In oneexample, the user of the terminal is an assessor performing a facilityassessment. In another example, the user of the terminal is a manager ofa resident care facility, viewing and analyzing the results of one ormore facility assessments.

It should be noted that the methods, systems, devices, and softwarediscussed above are intended merely to be examples. It must be stressedthat various embodiments may omit, substitute, or add various proceduresor components as appropriate. For instance, it should be appreciatedthat, in alternative embodiments, the methods may be performed in anorder different from that described, and that various steps may beadded, omitted, or combined. Also, features described with respect tocertain embodiments may be combined in various other embodiments.Different aspects and elements of the embodiments may be combined in asimilar manner. Also, it should be emphasized that technology evolvesand, thus, many of the elements are examples and should not beinterpreted to limit the scope of the invention.

It should also be appreciated that the following systems, methods, andsoftware may individually or collectively be components of a largersystem, wherein other procedures may take precedence over or otherwisemodify their application. Also, a number of steps may be requiredbefore, after, or concurrently with the following embodiments.

Specific details are given in the description to provide a thoroughunderstanding of the embodiments. However, it will be understood by oneof ordinary skill in the art that the embodiments may be practicedwithout these specific details. For example, well-known circuits,processes, algorithms, structures, waveforms, and techniques have beenshown without unnecessary detail in order to avoid obscuring theembodiments. It will be further understood by one of ordinary skill inthe art that the embodiments may be practiced differently in differentenvironments. For example, one environment may include a wirelessnetwork providing substantially constant access to the Internet from anassessor terminal; while another environment may include no wirelessconnection and may be implemented with more local data storage andbuffering capability.

Also, it is noted that the embodiments may be described as a processwhich is depicted as a flow diagram or block diagram. Although each maydescribe the operations as a sequential process, many of the operationscan be performed in parallel or concurrently. In addition, the order ofthe operations may be rearranged. A process may have additional stepsnot included in the figure.

Having described several embodiments, it will be recognized by those ofskill in the art that various modifications, alternative constructions,and equivalents may be used without departing from the invention.Accordingly, the above description should not be taken as limiting thescope of the invention, as described in the following claims.

1. A system for generating resource allocation determinations for anursing home facility, the system comprising: a computer operable toprovide a base assessment model modeled after a Quality IndicatorSurvey, wherein the Quality Indicator Survey comprises questionsaddressing a plurality of resident care areas, the plurality of residentcare areas relating to at least one of choices, dignity, abuse, health,personal property, or quality; a network portal interface operable toprovide a set of assessment questions to an assessor terminal, the setof assessment questions relating to at least a portion of the pluralityof resident care areas comprised in the Quality Indicator Survey,wherein the assessor terminal is operable to: provide the set ofassessment questions to an assessor; and receive responses to the set ofassessment questions based on answers provided to the assessor by a setof respondents, wherein the set of respondents comprises at least one ofa resident of the nursing home facility, a relative of the resident ofthe nursing home facility, or an employee of the nursing home facility;a response processing unit in operative communication with the networkportal interface and the computer and operable to generate qualityscores for each of the plurality of resident care areas based on theresponses, each quality score being indicative of a likelihood ofcitation in each resident care area as a function of data derived fromthe Quality Indicator Survey; a display generation unit in operativecommunication with the response processing unit and operable to displayeach quality score graphically in relation to its resident care area asa function of the data derived from the Quality Indicator Survey,wherein displaying each quality score comprises: displaying a first datarange in relation to a graphical scale, the first data rangerepresenting a range of scores in the resident care area indicative of asubstantial certainty of citation in the resident care area; displayinga second data range in relation to the graphical scale, the second datarange representing a range of scores in the resident care areaindicative of an uncertain likelihood of citation in the resident carearea; displaying a third data range in relation to the graphical scale,the third data range representing a range of scores in the resident carearea indicative of a substantial certainty of no citation in theresident care area; and displaying an indicator indicating a location ofthe quality score in relation to the graphical scale; and an allocationdetermination unit, in operative communication with the responseprocessing unit, and operable to formulate a resource allocationdetermination as a function of at least one of the quality scores.
 2. Amethod for generating information for determining resource allocation ina resident care facility, the method comprising: providing a set ofassessment questions to an assessor, the set of assessment questionsbeing: based on a base assessment model having questions relating to aplurality of resident care areas; and related to at least a portion ofthe plurality of resident care areas; receiving responses to at least aportion of the set of assessment questions; processing the responses togenerate an assessment dataset; generating a quality score for at leastone of the resident care areas, the quality score being based on theassessment dataset and indicative of a likelihood of citation in theresident care area associated with the quality score, as a function ofdata derived from the base assessment model; and displaying the qualityscore graphically in relation to the data derived from the baseassessment model.
 3. The method of claim 2, further comprising:providing a computer network portal interface, the computer networkportal interface being stored on a server and operable to interface withan assessor client terminal, wherein: providing the set of assessmentquestions comprises providing the set of assessment questions via thecomputer network portal interface to the assessor client terminal, andreceiving the responses comprises receiving the responses via thecomputer network portal interface from the assessor client terminal. 4.The method of claim 2, further comprising: generating data rangesassociated with the quality score as a function of the data derived fromthe base assessment model, wherein: a first data range represents arange of possible quality scores in the resident care area with asubstantially high likelihood of citation in the resident care area; asecond data range represents a range of possible quality scores in theresident care area with a substantially uncertain likelihood of citationin the resident care area; and a third data range represents a range ofpossible quality scores in the resident care area with a substantiallylow likelihood of citation in the resident care area.
 5. The method ofclaim 4, wherein displaying the quality score comprises: displaying agraphical scale indicating a full range of possible quality scores forthe resident care area; displaying the first data range in relation tothe graphical scale; displaying the second data range in relation to thegraphical scale; displaying the third data range in relation to thegraphical scale; and displaying an indicator indicating the location ofthe quality score in relation to the graphical scale.
 6. The method ofclaim 2, further comprising: deriving a likelihood of citation for eachof the possible quality scores based at least in part on a positivepredictive value of the possible quality score resulting in a citationaccording to the base assessment model.
 7. The method of claim 2,further comprising: deriving a citation threshold from the baseassessment model; and converting the citation threshold to a firstthreshold quality score, such that, for the resident care area, the baseassessment model indicates a substantially certain likelihood ofcitation when the generated quality score is below the first thresholdquality score and the base assessment model indicates a substantialcertainty of no likelihood of citation when the generated quality scoreis above the first threshold quality score.
 8. The method of claim 7,further comprising: displaying a graphical scale indicating a full rangeof possible quality scores for the resident care area; displaying afirst data range in relation to the graphical scale, the first datarange representing a range of the possible quality scores in theresident care area falling below the first threshold quality score;displaying a second data range in relation to the graphical scale, thesecond data range representing a range of the possible quality scores inthe resident care area falling above the first threshold quality score;and displaying an indicator indicating the location of the generatedquality score in relation to the graphical scale.
 9. The method of claim7, further comprising: deriving a second threshold quality score greaterthan the first threshold quality score, wherein the second thresholdquality score indicates a quality score for the resident care area wherethere is a maximum positive difference between an upper score and alower score, wherein the upper score indicates a composite positivepredictive value, according to the base assessment model, of a citationresulting from a range of the possible quality scores falling above thesecond threshold quality score, and wherein the lower score indicates acomposite positive predictive value, according to the base assessmentmodel, of a citation resulting from a range of the possible qualityscores falling below the second threshold quality score and above thefirst threshold quality score.
 10. The method of claim 9, furthercomprising: displaying a graphical scale indicating a full range ofpossible quality scores for the resident care area; displaying a firstdata range in relation to the graphical scale, the first data rangerepresenting a range of the possible quality scores in the resident carearea falling below the first threshold quality score; displaying asecond data range in relation to the graphical scale, the second datarange representing a range of the possible quality scores in theresident care area falling above the first threshold quality score andbelow the second threshold quality score; displaying a third data rangein relation to the graphical scale, the third data range representing arange of the possible quality scores in the resident care area fallingabove the second threshold quality score; and displaying an indicatorindicating the location of the generated quality score in relation tothe graphical scale.
 11. The method of claim 2, further comprising:providing a subsequent assessment question based on at least one of theset of responses.
 12. The method of claim 2, further comprising: hidinga subsequent assessment question based on at least one of the set ofresponses.
 13. The method of claim 2, wherein at least a portion of theresponses relate to personal observations made by the assessor.
 14. Themethod of claim 2, wherein at least a portion of the set of responsesrelate to answers provided to the assessor by residents residing at theresident care facility.
 15. The method of claim 2, wherein at least aportion of the set of responses relate to answers provided to theassessor by relatives of residents residing at the resident carefacility.
 16. The method of claim 2, wherein at least a portion of theset of responses relate to answers provided to the assessor by staff ofthe resident care facility.
 17. The method of claim 2, wherein at leasta portion of the set of responses relate to prior resident evaluationdata.
 18. The method of claim 2, further comprising: generating aquality score for each of a set of care sub-areas, wherein at least oneof the plurality of care areas comprises the set of care sub-areas. 19.The method of claim 2, wherein the generated quality score for the atleast one of the resident care areas is based in part on data relatingto another of the resident care areas.
 20. The method of claim 2,further comprising: analyzing the assessment dataset to generate ananalytic dataset.
 21. The method of claim 20, wherein: analyzing theassessment dataset comprises statistically processing the assessmentdataset to generate predictive data for use in making a citationprediction, and the analytic dataset comprises the citation prediction.22. The method of claim 2, further comprising: refining the set ofquality scores based on a set of comparison data.
 23. The method ofclaim 2, further comprising: refining the set of quality scores based ona set of previously-acquired assessment results.
 24. The method of claim2, wherein the citation comprises an initiation of a legal proceedingrelating to a sub-standard practice of the resident care facility. 25.The method of claim 2, wherein the base assessment model comprises: apredefined assessment dataset; and a plurality of prior assessmentdatasets, each prior assessment dataset having been generated fromresponses to prior assessments.
 26. The method of claim 25, whereingenerating the quality score comprises: generating the quality score asa function of the predefined assessment dataset; and refining thequality score based on at least a portion of the prior assessmentdatasets.
 27. The method of claim 2, further comprising: formulating aresource allocation determination as a function of the quality score.28. The method of claim 27, wherein the resource allocationdetermination is indicative of an allocation of resources operable toreduce the likelihood of citation in the resident care area associatedwith the quality score.
 29. The method of claim 27, wherein the resourceallocation determination is indicative of an allocation of resourcesamong a plurality of resident care areas, resident care sub-areas, orresident care facilities.
 30. The method of claim 2, further comprising:encrypting the set of assessment data.
 31. The method of claim 2,wherein: the base assessment model comprises the Quality IndicatorSurvey; the citation comprises a trigger for a Stage II investigation;and the likelihood of citation comprises a likelihood that a furthercitation will be issued as a result of the Stage II investigation.
 32. Acomputer-readable storage medium having a computer-readable programembodied therein for directing operation of a computer interface, thecomputer-readable program including instructions for generatinginformation for determining resource allocation in a resident carefacility in accordance with the following: providing a set of assessmentquestions to an assessor via the computer interface, the set ofassessment questions being based on a base assessment model havingquestions relating to a plurality of resident care areas, and related toat least a portion of the plurality of resident care areas; receiving,via the computer interface, responses to at least a portion of the setof assessment questions, at least a portion of the responses relating toanswers provided to the assessor by a set of respondents; processing theresponses to generate an assessment dataset; and generating a qualityscore for at least one of the resident care areas, the quality scorebeing based on the assessment dataset and indicative of a likelihood ofcitation in the resident care area as a function of data derived fromthe base assessment model.
 33. The computer-readable storage medium ofclaim 32, wherein the instructions for generating information fordetermining resource allocation in the resident care facility arefurther in accordance with providing a computer network portal interfaceoperable to interface with an assessor client terminal.
 34. Thecomputer-readable storage medium of claim 32, wherein the instructionsfor generating information for determining resource allocation in theresident care facility are further in accordance with displaying thequality score graphically in relation to the data derived from the baseassessment model.
 35. The computer-readable storage medium of claim 32,wherein the instructions for generating information for determiningresource allocation in the resident care facility are further inaccordance with analyzing the assessment dataset to generate an analyticdataset.
 36. The computer-readable storage medium of claim 32, whereinthe instructions for generating information for determining resourceallocation in the resident care facility are further in accordance withformulating a resource allocation determination as a function of thequality score.